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Co-authored-by: Alexa Kreizinger <[email protected]> Signed-off-by: esmerel <[email protected]>
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concepts/data-pipeline/filter.md

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# Filter
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In production environments you want to have full control of the data being collected.
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In production environments you need full control of the data you're collecting.
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Filtering lets you alter the collected data before delivering it to a destination.
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```mermaid
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style C stroke:darkred,stroke-width:2px;
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```
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Filtering is implemented through plugins. Each available filter could be used to
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match, exclude or enrich your logs with specific metadata.
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Filtering is implemented through plugins. Each available filter can be used to
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match, exclude, or enrich your logs with specific metadata.
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Fluent Bit support many filters. A common use case for filtering is Kubernetes
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deployments. Every pod log needs the proper metadata associated.
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deployments. Every pod log needs the proper metadata associated with it.
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Like input plugins, filters run in an instance context, which has its own independent
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configuration. Configuration keys are often called _properties_.

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